BrahMap

A scalable and modular map-making framework for the CMB experiments

Documentation | Quick Start | Examples

This project is currently under active development!!!

BrahMap is a scalable and modular map-making framework for CMB experiments. It features a user-friendly Python interface for the linear operators used in map-making. The Python interface seamlessly handles the workflow while delegating the heavy computations to highly optimized C++ extensions. In addition to the core linear operators, BrahMap offers a wrapper for Generalized Least Squares (GLS) map-making using a Preconditioned Conjugate Gradient (PCG) solver. BrahMap is also fully integrated with litebird_sim through dedicated wrappers.

For a quick introduction to map-making with BrahMap, refer to the quick start guide. For a complete reference to the BrahMap API, refer to the API reference. Complete example notebooks and scripts can be found here.

You can find detailed information on the implementation and features of BrahMap at arXiv:2501.16122.

Installation

The versions of the dependencies for BrahMap are quite flexible. If you intend to use BrahMap alongside other packages (like litebird_sim), we recommend installing BrahMap after you have installed those packages in the same environment.

BrahMap requires an MPI library to compile the C++ extensions. By default, it uses the mpicxx compiler wrapper for this task. However, you can override this default by setting the MPICXX environment variable to your preferred compiler. To install BrahMap, please follow these steps:

# Clone the repository
git clone https://github.com/anand-avinash/BrahMap.git

# Enter the directory
cd BrahMap

# Set the compiler you want to use (optional)
export MPICXX=mpiicpc

# Install the package
pip install .

# Alternatively, do an editable installation for development purpose
# followed by `pre-commit` install
pip install -e .
pre-commit install

Note

BrahMap uses Setuptools to build the C++ extensions. By default, it generates the compilation command by gathering various environment variables. You can customize the compilation flags used during the installation by setting the CXXFLAGS, CPPFLAGS, and LDFLAGS environment variables.

Benchmarking

BrahMap includes a comprehensive benchmarking suite to evaluate the performance of its numerical routines and linear operators. The benchmarks are based on pytest-benchmark and support both serial and MPI-parallel execution.

For detailed instructions on how to run and customize the benchmarks, refer to the benchmarks documentation.

Citation

This work can be cited with:

@misc{anand2025brahmap,
      title={\texttt{BrahMap}: A scalable and modular map-making framework for the CMB experiments}, 
      author={Avinash Anand and Giuseppe Puglisi},
      year={2025},
      eprint={2501.16122},
      archivePrefix={arXiv},
      primaryClass={astro-ph.CO},
      url={https://arxiv.org/abs/2501.16122}, 
}

Acknowledgement

This work is supported by Italian Research Center on High Performance Computing, Big Data and Quantum Computing (ICSC), project funded by European Union - NextGenerationEU - and National Recovery and Resilience Plan (NRRP) - Mission 4 Component 2 within the activities of Spoke 3 (Astrophysics and Cosmos Observations).